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Boston Forex Trading: Profits With Sustainability And Green Investments – BOSTON, January 6, 2015 // — Boston Technologies, a leading innovator of FX trading technology and a provider of high-level liquidity for institutional and retail brokerage firms powered by Forexware, today announced the merger of FXStreet and FXStreet’s Forex distribution. The news. The news feed provides real-time coverage of the latest Forex news for Boston Technologies developed by Forexware’s MetaTrader 4 clients.
FXStreet’s team of journalists and forex experts have created the Forex News feature to fill the gap in the market for news related to currencies, indicators, central banks, stocks, gold and oil. Coverage includes significant moves in the most traded pairs, including majors, minors, and major crosses. Forex News also includes charts as a supplement to the news. News Feed generates more than 100 stories every weekday and is available in multiple languages, including English, Chinese, Japanese, Russian, Arabic, German, Indonesian, Spanish and Turkish.
Boston Forex Trading: Profits With Sustainability And Green Investments
“At Boston Technologies Powered by Forexware, we are constantly looking at partner solutions that can strengthen our portfolio and have an immediate impact on our customers,” said Natalia Hunik, Vice President of Global Sales, Boston Technologies Powered by Forexware. “We believe FXStreet’s multilingual news suite resonates very strongly with our clients and adds value to their businesses.”
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A real-time news feed is delivered to the websites of FX brokers via an RSS feed or distributed directly to MetaTrader 4 trading terminals via the built-in MetaTrader 4 module.
“Our goal is to be the primary source of information for forex traders by providing accurate and timely technical and fundamental information on how currencies are moving,” said Carolina May, CEO of FXStreet. “Boston Technologies Powered by Forexware is a recognized leader in the industry and we know this partnership is a strategic step in the right direction for both companies.”
About Boston Technologies Powered by Forexware, Inc. Boston Technologies Powered by Forexware is a leading global innovator and provider of trading technology and software for foreign exchange and other OTC trading instruments for institutional and retail brokerage firms. In 2014, Boston Technologies merged with Forexware, a software developer specializing in B2B trading applications and FX enterprise solutions, to create a single global leader in institutional trading technology. The firm’s comprehensive portfolio includes a Start Your Own Broker package for novice traders, a Tier 1 liquidity connector for institutional clients, risk management for money managers and precious metals trading. The company is headquartered in Boston with offices in New York, London, Tokyo and Shanghai. For more information, visit: www.bostontechnologies.com.
About FXStreet FXStreet was founded in January 2000. As its distinctive trademark, the website prides itself on its unwavering commitment to always provide objective and unbiased information and empower its users to make better and more confident decisions. Real-time quotes, news, updates and interactive chats with experts from all over the world are some of the most popular content on the website. FXStreet has been able to attract the cooperation of the entire Forex industry, from professionals and small companies to Forex brokers and investment banks.
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Spatiotemporal Characterization of Ethnic Toponyms Based on Spatial Information Entropy at the Village Level in Northeast China
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Received: February 1, 2020 / Revised: April 3, 2020 / Accepted: April 17, 2020 / Published: April 26, 2020
The machine learning paradigm promises traders to reduce uncertainty through better predictions made by more sophisticated algorithms. We ask about the identified effects of uncertainty and complexity on the overall market level. We analyzed nearly one billion trades in eight currency pairs (2007–2017) and showed that the increase in algorithmic trading is associated with more complex trailing sequences and predictable structures in bid-ask spreads. However, algorithmic engagement is also associated with future uncertainty, which seems counterintuitive at first glance. At the micro-level, traders use algorithms to reduce local uncertainty by creating complex algorithmic patterns. It requires prior structure and complexity. At the macro level, increased overall complexity means more combinatorial possibilities and thus more uncertainty about the future. The chain rule of entropy shows that uncertainty is reduced when trading at the level of the fourth position behind the dollar, and new uncertainty begins to appear at the level of the fifth position behind the dollar (“pip-trading”). In summary, our information theoretic analysis helps to clarify whether the apparent contradiction between decreasing micro-level uncertainty and increasing macro-level uncertainty is the result of an inherent relationship between complexity and uncertainty.
The information revolution has changed not only business, economics, politics and socio-cultural behavior, but also the way financial markets operate. Looking at the hustle and bustle of trading floors just a decade ago and comparing them to the smooth noise of today’s computational trading floors shows that algorithmic trading has had a profound effect on the way financial assets change hands. In this study, we look for observable signatures that evidence changes in the nature of trade dynamics over the last decade. We find that the overall emerging trade dynamics have become more predictable, more complex and uncertain at the same time. We choose the currency market for analysis because it has experienced a clear and precise growth in algorithmic trading.
Generally, traders use algorithmic automation to make their local dynamics reliable and predictable. A large literature also suggests that trade accelerates, but we are not concerned with this in this study. Prediction accuracy is the name of the game in the currently dominant machine learning paradigm [1]. Most digital automated data processes, including bots, trading algorithms and all types
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